Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
huggingpics
Eval Results (legacy)
Instructions to use sanali209/nsfwfilter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanali209/nsfwfilter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sanali209/nsfwfilter") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("sanali209/nsfwfilter") model = AutoModelForImageClassification.from_pretrained("sanali209/nsfwfilter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0645b3a36172611dc2d949b22fc2c8fe831b561c691d4b88a7c48abe9faf7bd3
- Size of remote file:
- 6.7 kB
- SHA256:
- e2fffb16306320c60e8acc1f593cddf810c43cb196c727bd7f87d98f4449c170
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